Socioeconomic Variability in Human Fecundity

Fecundity is a fundamental but poorly understood driver of human population dynamics. Even the most basic fecundity-related outcomes are difficult to measure in real-world populations because of cost, ethics, and disciplinary mores. As a result, most of what we think we know about these outcomes at the population level is based (a) on self-reported assessments of fertility and/or duration attempting pregnancy,(b) on creative inferential designs applied to small sample prospective studies with pre-conception enrollment, or (c) on animal models (Chandra et al. 2013; Hardy & Hardy 2014; Keiding 2012). These measurement approaches have proved most useful in identifying extreme outcomes—for example, levels and trends in the fraction of a population that is infertile or subfecund (Chandra & Stephen 1998; Gurunath 2011; Scheike et al. 2008; Thoma et al. 2013).

There are significant gaps in our knowledge. We have almost no measurement at the population level that sheds light on distinct drivers of fecundity levels—eg, germ cell quality, probabilities of fertilization, embryo implantation, and pregnancy loss. Biomedical research on recruited samples or couples using assisted reproductive technology fills important components of this gap (see for example, Hardy and Hardy 2014; Norwitz et al. 2001; Rolland et al. 2012; Snijder et al. 2011; Wang et al. 2003; Wilcox et al. 1988; Velez et al. 2015), though the estimates from this research are rarely able to capture early pregnancy for more than a few hundred cases and/or rarely come from population samples.

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Recommended citation: Nobles, J., Hamoudi, A., Nowak, R., Landau, E., Baron, A., Brittingham, J., & Mason, B. (2018, April). Socioeconomic Variability in Human Fecundity. In PAA 2018 Annual Meeting. PAA.